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Action Research Plan

Master of Science in Education, Walden University

EDUC 6733: Action Research for Educators

August 9, 2020

Part F: Methodology: Collecting Data

Action research is a systematic inquiry into one’s own practice that allows teachers to study their own classrooms and instructional methods (Mertler, 2020). By using various data collection methods, I was able to expand and strengthen the validity and conclusion of my study. Research shows, data-driven pedagogical decisions have a positive impact on their students’ learning outcomes (Clark, Galstaun, Reimann, & Handal, 2020). For this study I chose to use quantitative measures, a critical friend group, as well as field notes as data collection tools.

The use of quantitative measures was a vital aspect of this study. The use of student’s NWEA MAP scores, and their scores from their pre/post reading foundational and oral language assessments provided me with statistical data to evaluate; providing clear and objective results. NWEA MAP scores were used to determine which students were eligible for the study. With the help of my colleagues, I decided it would be best to choose students whose scores placed them in the LoAvg category. I originally planned to use students who scored significantly lower than their peers because they need immediate remediation and support. My colleagues and I arrived at the new decision after discussing who would benefit more from remedial instruction, and which students possesses enough skills and English proficiency to properly navigate the Imagine Learning platform. While my colleagues and I did not all agree with this decision, it was important to produce valid and reliable data. One change we did all agree on was the decision to decrease the number of participants from 6 to 4 due to the amount of time it takes to assess students. Using students who lack basic English proficiency and early literacy skills such as phonological awareness, letter identification, matching letters to sounds, and concepts of print; would significantly skew my data and results. After choosing participants, the nest step was to determine their reading and oral language abilities. The student’s received pre assessments to determine their baseline scores. These assessments acted as formative assessments to determine the student’s reading and language capabilities prior to using the Imagine Learning Language and Literacy program. Post assessments were administered to students as summative assessments to determine the amount of student growth and achievement following the intervention.

In addition to quantitative measures, I also used field notes and a critical friend group throughout this study. These two data tools worked together. The members of my critical friend group are a few of my grade level teammates. Because we team teach, my colleagues were able to observe student’s growth in language and reading across various subjects, and jot down observed behaviors. We collaborated weekly to compare our findings and student data. The participants received instruction from the Imagine Learning platform 3 days a week, the remainder 2 days, the students engaged in hands on cooperative learning activities. To maximize student potential and the validity of my data, I placed students in a small group and assigned cooperative learning activities such as matching games and puzzles that required the participants to use both language and reading foundational skills. These activities provided me with opportunities to observe students and take field notes.

Collaborating with my colleagues has been the highlight of this process for me. One member of my critical friend group is a 2nd grade teacher. As a past 2nd grade teacher, I recall having students enter the classroom with no alphabet knowledge and phonics skills due to language barriers. The deficits my students have are not limited to this small group. It is an issue across many classrooms in my school. In our diverse school, students enter the classroom in all grades with little English proficiency and no knowledge of basic reading foundational skills such as phonemic awareness. I am not the only teacher faced with these issues, so it is extremely beneficial to include and collaborate with my colleagues throughout this process. The timeline I created was a critical component of my action plan. Without the use of a timeline, the relationship between the data cannot be observed. The timeline helped me stay organized and acted as a timetable for keeping me on schedule with assessments and data analyzation. It made my weekly objectives concise, clear and achievable.

Part G: Methodology: Analyzing and Graphing Data Using Triangulation

Comparing quantitative and qualitative data results is important to determine if the data tools have yielded similar results and to determine any patterns in data measures. When comparing the three sets of data, my colleagues and I focused on and discussed the data sets individually first. We wanted to analyze each data set independently before comparing them to one another. Next, we compared the data sets, and looked for any similarities, differences and patterns. Lastly, we used the information from our data analyzes to determine if the action research question has been answered and what other lingering questions we still have. By comparing data sets, we were able to determine to what effect computer assisted language programs effect Kindergarten English Language Learners. The data sets yielded similar results. Students showed growth, however, it was not consistent nor significant.

RF= Reading Foundational OL= Oral Language

July 20th July 27th August 3^rd August 6th

Week 1 Week 2 Week 3 Week 4

Pre assessments

Student 1:RF-45/100 Student 1:RF-40/100 Student 1:RF-45/100 Student 1:RF-50/100

OL- 6/10 OL- 6/10 OL- 8/10 OL- 8/10

Student 2:RF- 30/100 Student 2:RF- 30/100 Student 2:RF- 25/100 Student 2:RF- 30/100

OL-5/10 OL-5/10 OL-6/10 OL-6/10

Student 3:RF-65/100 Student 3:RF-65/100 Student 3:RF-80/100 Student 3:RF-80/100

OL-7/10 OL-7/10 OL-8/10 OL-8/10

Student 4:RF-50/100 Student 4:RF-55/100 Student 4:RF-55/100 Student 4:RF-55/100

OL-4/10 OL-4/10 OL-6/10 OL-6/10

This is a chart showing student’s Reading Foundational and Oral Language assessment scores.

I used a gradebook to keep track of student weekly scores and then added those scores to a chart weekly. I decided to create a chart because using charts and graphs to visualize complex data is easier than looking at spreadsheets or reports (Ifenthaler & Erlandson, 2016). I created a chart to provide a visualization of how we monitored student progress over the course of the study. The chart displays students Reading Foundational assessment scores and their Oral Language assessment score following a picture naming test. These scores fluctuated over the course of 4 weeks. With the exception of one student, majority of the students Reading Foundational scores remained the same, or either decreased and increased by 5. This means that after receiving literacy and language instruction via the Imagine Learning program, the students were only able to answer 1 or more questions correctly on same assessment consistently for 3 weeks. Student #3 began the study with the highest scores and showed the most growth throughout the process. However, the student did not score in the 90th range on either assessment. Like most students, this student showed growth but no achievement. When comparing field notes, the results were similar. During cooperative learning activities and independent work time, students were observed using more language skills; however, it was common for students to be too specific, and to name an objects function versus its name. While completing an activity for community helpers, I observed and described in my field notes how student #2 constantly referred to the grocery store as Wal-Mart, versus acknowledging it was simply a store or market. During week three’s analyzation meeting, one colleague argued that it appears student’s confidence grew, resulting in them becoming more verbal but the students did not acquire any new languages skills per se.

“To what extent can small group instruction, 3 times a week, for 20 minutes using Imagine Learning’s digital language and literacy program improve and accelerate student reading and language proficiency?”. I do believe my data answered my question. The data revealed that digital literacy tools can have a positive effect on student learning. I was surprised by the results of my data. I entered this process believing Imagine Learning is a great resource and its instruction would significantly improve the language and reading skills of my young learners. Majority of the students did show growth in their scores, as well as increased their overall language usage. Unfortunately, the growth observed was not very measurable. Because students responded well to the intervention, in the future I plan to increase the number of days the students use the platform, as well as increase the amount of time spent on the platform, in hopes of yielding more positive results.

My data analysis and results are similar to the findings in my literature review. My literature review helped me understand that digital literacy tools are beneficial for language learners due to support from narration, pictures, and audio. My literature review also revealed students in grades K-5 using the Imagine Language and Literacy during the 2016-2017 school year, maintained their reading and language growth after a full year of instruction the program (Prybil, 2018). My results were consistent with this study. The students enjoyed using the Imagine Learning platform. In addition to boosting student engagement, the system appears to have a positive effect on students in reading and language skills, despite lack of overall student achievement. The results from my research are important for me to share with other colleagues to determine ways to maximize the Imagine Learning Language and Literacy program to better support student growth and achievement.

References

Ifenthaler, D., & Erlandson, B. E. (2016). Learning with data: Visualization to support teaching,

learning, and assessment. Technology, Knowledge And Learning: Learning

Mathematics, Science And The Arts In The Context Of Digital Technologies, 21(1), 1-3.

doi:10.1007/s10758-015-9273-5

Kennedy-Clark, S., Galstaun, V., Reimann, P., & Handal, B. (2020). Using Action Research to Develop Data Literacy in Initial Teacher Education. Journal of Teacher Action Research, 6(2) , 4–25.

Mertler, C. A. (2020). Action research: Improving schools and empowering educators (6th ed.).

Sage.

Prybil, B. D. (2018). Measuring reading growth of elementary students using a digital learning

resource (Order No. 10812311) [Doctoral Dissertation, Southern Illinois University].

ProQuest Central; ProQuest Dissertations & Theses Global.

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